Triple
T12853567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Champaign Unit 4 School District |
E307388
|
entity |
| Predicate | offersMealProgram |
P178
|
FINISHED |
| Object | school breakfast program |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: school breakfast program | Statement: [Champaign Unit 4 School District, offersMealProgram, school breakfast program]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersMealProgram Context triple: [Champaign Unit 4 School District, offersMealProgram, school breakfast program]
-
A.
offersMeal
Indicates that one entity provides or makes available a meal to another entity.
-
B.
offersProgram
chosen
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
-
C.
offersProgramCategory
Indicates that an entity provides or makes available a specific category of program.
-
D.
offersProgramsIn
Indicates that an institution or provider makes educational or training programs available in a particular field, subject, or area.
-
E.
offersCreativePrograms
Indicates that an entity provides or makes available programs or activities designed to foster creativity or artistic expression for another entity or audience.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa3002881908000357b1f95a3ac |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:36 p.m.